Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (NLP/AI): Designing and building models and ML pipelines for user and conversation understanding for Copilot with an accent on intent detection, topic classification, and personalization. Focus on developing transformer-based models, optimizing RAG patterns, and deploying scalable production-grade inference pipelines.

Location: Mountain View, United States

Salary: $158,400 – $258,000 per year

Company

hirify.global AI is building advanced systems that integrate artificial intelligence across agents, applications, and infrastructure to empower users worldwide.

What you will do

• Design, train, and deploy ML models for NLU tasks including intent detection, topic classification, and conversation summarization.
• Architect scalable, production-grade training and inference pipelines using Spark, Databricks, and Azure ML.
• Develop transformer-based models and maintain embedding pipelines and vector databases for semantic search and retrieval.
• Drive rigorous offline and online experimentation to iterate on architectures and improve key product metrics.
• Partner with data engineers, data scientists, and product teams to translate research insights into shipped features.
• Monitor production model performance, diagnose regressions, and resolve scalability and reliability bottlenecks.

Requirements

• Must be based in the United States.
• Bachelor’s degree in CS, Statistics, or related field with 4+ years of experience (or Master's with 3+ years, or PhD with 1+ year).
• Proven experience in NLP and modern transformer architectures for classification, encoding, and summarization.
• Proficiency in Python and ML frameworks such as PyTorch or Hugging Face Transformers.
• Experience with text embedding models, vector databases, and retrieval-augmented generation (RAG) patterns.
• Familiarity with distributed training, model optimization, and serving ML models at scale.

Nice to have

• Experience with search ranking, relevance modeling, or information retrieval systems.
• Experience building end-to-end ML pipelines from data ingestion through deployment.

Culture & Benefits

• Work environment driven by a growth mindset, innovation, and collaboration.
• Culture of inclusion based on respect, integrity, and accountability.
• Comprehensive corporate benefits package including health and retirement plans.